A fi ve layer sensor architecture for autonomous robots in indoor environments

Autonomous mobile service robots for transportation tasks in indoor environments e.g. multistory buildings, have to act in normal dy- namic environments but with a huge number of components. The robots total repertoire of skills is high according to the complexity of the building and its respective task. Difficult tasks can only be achieved on the base by immediate sensing of the environment. This paper describes a fi ve layer sen- sor architecture with an integrated world model for multistory buildings. In contrast to grid based approaches we use a feature based approach. The sensor architecture as well as the evaluation modules of the sensor data are based on natural landmarks. The key features of the sensor architecture are reuseability, modularity and portability to other multistory buildings as well as extendibility with different sensors.